Researchers create LiveBench benchmark to measure AI response accuracy.

Researchers develop new LiveBench benchmark for measuring AI models’ response accuracy

A group of researchers has developed a new benchmark called LiveBench to evaluate large language models’ question-answering capabilities. The benchmark, released under an open-source license, aims to address challenges like contamination and accuracy issues in existing benchmarks. LiveBench provides tasks with answers unlikely to be in training datasets to avoid contamination. It also includes prepackaged answers for evaluation questions, eliminating the need for external AI systems. The benchmark includes 960 questions across six categories and is regularly updated to prevent cheating. The creators argue that existing methods of using external LLMs for evaluation have limitations and may lead to inaccurate results. LiveBench aims to provide a more reliable and accurate evaluation method for language models.

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